There is currently scarce information on the occurrence and distributions of Polycyclic Aromatic Hydrocarbons (PAHs) in the air from industrial estates in Nigeria. Hence, the present study aims to evaluate the extent and sources of pollution of polycyclic aromatic hydrocarbons in the air from some industrial estates in Lagos and Ogun States, Nigeria. Ten air samples have been collected from the industrial estates in Lagos (Ogba and Ilupeju) and ten from Ogun (Agbara and Ota) between October and November, 2014, using low volume air sampler. Also five further air samples have been collected from Epe town, located in the outskirts of Lagos, where there are no industrial activities to serve as control. The concentrations and distributions of 20 target Polycyclic Aromatic Hydrocarbons (PAHs) in the air samples have been determined by gas chromatography-mass spectrometry. The concentration of ∑20PAHs ranged from 89.20 to 96.48 ng/m3 (with an average of 92.84 ng/m3) and 72.52 to 142.91 ng/m3 (with an average of 107.72 ng/m3) in the air samples from Lagos and Ogun industrial estates, respectively. The air from the control site has a total ∑20PAHs concentration of 19.55 ng/m3 (9.78 ng/m3 in average). When compared with global data, these values show that the air samples have been moderately polluted. PAHs in most air samples are mainly from pyrolytic sources, which may have resulted from diesel fuel combustion and high vehicular emissions, typical of industrial activities in the area.

Organic aerosol (OA) emitted from biomass burning (BB) impacts air quality and global radiation balance. However, the comprehensive characterization of OA remains poorly understood because of the complex evolutionary behavior of OA in atmospheric processes. In this work, smoke particles were generated from rice straw combustion. The effect of OH radicals photooxidation on size distribution, light absorption, and molecular compositions of smoke particles was systematically investigated. The results showed that the median diameters of smoke particles increased by a factor of approximately 1.2 after photooxidation. In the particle compositions, although both non-polar fractions (n-hexane-soluble organic carbon, HSOC) and polar fractions (water-soluble organic carbon, WSOC) underwent photobleaching after aging, the photobleaching properties of HSOC (1.87–2.19) was always higher than that of WSOC (1.52–1.33). Besides, the light-absorbing properties of HSOC were higher than that of WSOC, showing a factor of approximately 1.75 times for mass absorption efficiency at 365 nm (MAE₃₆₅). Consequently, the simple forcing efficiency (SFE) caused by absorption showed that HSOC has higher radiation effects than WSOC. After photooxidation, the concentration of 16 PAHs in HSOC fractions significantly decreased by 15.3%–72.5%. In WSOC fractions, the content of CHO, CHONS, and CHOS compounds decreased slightly, while the content of CHON compounds increased. Meantime, the variations in molecular properties supported the decrease in light absorption of WSOC fractions. These results reveal the aging behavior of smoke particles, then stress the importance of non-polar organic fractions in particles, providing new insights into understanding the atmospheric pollution caused by BB smoke particles.

Many studies revealed the rapid decline of atmospheric PM₂.₅ in Beijing due to the emission control measures. The variation of particle number concentration (PN) which has important influences on regional climate and human health, however, was rarely reported. This study measured the particle number size distributions (PNSD) in 3–700 nm in winter of Beijing during 2013–2019. It was found that PN decreased by 58% from 2013 to 2017, but increased by 29% from 2017 to 2019. By Positive matrix factorization (PMF) analysis, five source factors of PNSD were identified as Nucleation, Fresh traffic, Aged traffic + Diesel, Coal + biomass burning and Secondary. Overall, factors associated with primary emissions were found to decrease continuously. Coal + biomass burning dominated the reduction (65%) among the three primary sources during 2013–2017, which resulted from the great efforts on emission control of coal combustion and biomass burning. Fresh traffic and Aged traffic + Diesel decreased by 43% and 66%, respectively, from 2013 to 2019, as a result of the upgrade of the vehicle emission standards in Beijing-Tianjin-Hebei area. On the other hand, the contribution from Nucleation and Secondary decreased with the reduction of gaseous precursors in 2013–2017, but due to the increased intensity of new particle formation (NPF) and secondary oxidation, they increased by 56% and 70%, respectively, from 2017 to 2019, which led to the simultaneously increase of PN and particle volume concentration. This study indicated that NPF may play an important role in urban atmosphere under continuous air quality improvement.

Hourly PM₂.₅ speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM₂.₅ components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM₂.₅ water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMFwₕₒₗₑ). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMFwₕₒₗₑ solution. After removing event data, PMF modeling was conducted for individual months (PMFₘₒₙₜₕ) and the 4-year period (PMF₄₋yₑₐᵣ), respectively. PMFₘₒₙₜₕ solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF₄₋yₑₐᵣ solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.

Air pollution is among the top risk faced by people around the world, and therefore combating it is among the top priorities. It begins with identifying the sources that contribute the most to local air pollution to prioritize their control. There are advanced methods for source identification and apportionment, but such methods are not available in many low-income countries and not everywhere in all high-income countries. We propose a simplified method by using source the signatures to help obtain information about the local source contribution if no other methods are available. Using low-cost monitors, particle mass (PM₂.₅) and carbon monoxide (CO) concentrations were measured and the ratio of CO/PM₂.₅ was determined. We investigated outdoor and indoor sources, including vehicular exhaust, combustion of biomass, incense and mosquito coil burning, and cigarette smoking. The results show that the ratios differed significantly between certain pollutant sources. Compressed natural gas (CNG) engines have a high ratio (mean value of 972 ± 419), which is attributed to relatively low PM₂.₅ emissions, while ship emissions and cigarette smoke recorded a relatively low ratio. Most traffic emissions recorded higher ratios than those of bushfire emissions, and ratios of most outdoor pollutant sources were much higher than those of indoor pollutant sources. There is a clear trend for ratios to decrease from high to low for CNG, petrol, diesel for buses, and fuel for ships. Our results suggest that the ratio of CO/PM₂.₅ can be used as an effective method to identify pollution sources.

Inhalation of respirable silica particles can cause serious lung diseases (e.g., silicosis and lung cancer), and the toxicity of respirable silica is highly dependent on its crystal form. Common combustion processes such as coal and biomass burning can provide high temperature environments that may alter the crystal forms of silica and thus affect its toxic effects. Although crystalline silica (i.e., quartz, tridymite, and cristobalite) were widely found at different temperatures during the burning processes, the sources and crystal transformation pathways of silica in the burning processes are still not well understood. Here, we investigate the crystal transformation of silica in the coal and biomass combustion processes and clarify the detailed transformation pathways of silica for the first time. Specifically, in coal burning process, amorphous silica can transform into quartz and cristobalite starting at 1100 °C, and quartz transforms into cristobalite starting at 1200 °C; in biomass burning process, amorphous silica can transform into cristobalite starting at 800 °C, and cristobalite transforms into tridymite starting at 1000 °C. These transformation temperatures are significantly lower than those predicted by the classic theory due to possibly the catalysis of coexisting metal elements (e.g., aluminum, iron, and potassium). Our results not only enable a deeper understanding on the combustion-induced crystal transformation of silica, but also contribute to the mitigation of population exposure to respirable silica.

Trace metal (loid) contamination in the atmosphere is widely monitored, but there is a gap in understanding its long-term patterns, especially in North China, which is currently a global contamination hotspot mainly caused by heavy industry emissions and coal combustion. Herein, historical trends of atmospheric As, Cd, Cr, Cu, Hg, Ni, Pb and Zn contamination in North China over the past ∼500 years are comparatively studied with sediment cores from two subalpine lakes (Gonghai and Muhai). Arsenic, Pb, Cd and Hg were main pollutants according to Pb isotopes and enrichment factors. Mercury contamination has increased continuously since the late 1800s and increasing As, Pb and Cd contamination started in the 1950s in Gonghai. In contrast, the contamination in Muhai lagged two decades for As, Cd and Pb and a half-century for Hg behind that in Gonghai, although the trends were similar. This contamination lag was attributed to the low sensitivity of Muhai sediment to early weak atmospheric metal contamination under 2.1-fold higher detrital sedimentation. As, Pb and Cd contamination has intensified since the 1980s, and the metals showed similar sedimentary fluxes in the cores. However, sedimentary fluxes of Hg contamination were 3.4-fold higher in Gonghai than in Muhai due to combination with organic matter. No obvious Cr, Cu and Ni contamination in the cores was mainly because of the low atmospheric deposition from anthropogenic sources relative to detrital input, although some of their atmospheric emissions were higher than those of As, Cd and Hg. Atmospheric As, Pb and Cd contamination was mainly from domestic sources of coal combustion and nonferrous smelting. Mercury contamination was mainly from global and Asian sources in the first half of the 20th century, and domestic emissions gradually dominated Hg contamination after the mid-1900s.

Exposure to electronic and electrical waste (e-waste) has been related to a few adverse health effects. In this study, sediment samples from an e-waste recycling town in China were collected, and aryl hydrocarbon receptor (AhR) agonists in the samples were identified using an effect-directed analysis (EDA) strategy. The CBG2.8D cell line reporter gene bioassay was used as a toxicity test, while suspect screening against chemical databases was performed for potential AhR agonist identification where both gas chromatography- and liquid chromatography-high resolution mass spectrometry analyses were run. When the original sample extract showed high AhR-mediated activity, sample fractionation was performed, and fractions exhibiting high bioactivity were chemically analyzed again to reveal the corresponding AhR agonists. In total, 23 AhR agonists were identified, including 14 commonly known ones and 9 new ones. Benzo [k]fluoranthene and 6-nitrochrysene were the dominant AhR agonists, covering 16–71% and 2.7–12%, respectively, of the AhR activation effects measured in the parent extracts. The newly identified AhR-active chemicals combined explained 0.13–0.20% of the parent extracts’ effects, with 7,12-dimethylbenz [a]anthracene and 8,9,11-trimethylbenz [a]anthracene being the major contributors. A diagnostic isomer ratio analysis of polycyclic aromatic hydrocarbons suggested that the major source of AhR agonists identified in these e-waste related sediment samples were probably petroleum product combustion and biomass combustion. In the future, for a more comprehensive AhR agonist investigation, in-house chemical synthesis and purification, and, when necessary, a secondary sample fractionation, would be beneficial.

Although biomass fuel has always been regarded as a source of sustainable energy, it potentially emits polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). This study investigated PCDD/F emissions from industrial boilers fired with three types of biomass fuel (i.e., bagasse, coffee residue, and biomass pellets) via stack sampling and laboratory analysis. The measured mass concentrations of PCDD/Fs varied among the boilers from 0.0491 to 12.7 ng Nm⁻³ (11% O₂), with the calculated average international toxic equivalent quantity (I-TEQ) from 0.00195 to 1.71 ng I-TEQ Nm⁻³ (11% O₂). Some of them were beyond the limit value for municipal waste incineration. 2,3,4,7,8-PeCDF could be used as a good indicator of dioxin-induced toxicity of stack flue gases from biomass-fired boilers. The PCDFs/PCDDs ratios were more than 1, likely indicating the formation of dioxins in the boilers favored by de novo synthesis. The emission factor (EF) of total PCDD/Fs averaged 5.35 ng I-TEQ kg⁻¹ air-dry biomass (equivalent to 39.0 ng kg⁻¹ air-dry biomass). Specifically, the mean EF was 6.94 ng I-TEQ kg⁻¹ (52.6 ng kg⁻¹) for biomass-pellet-fired boiler, 11.8 ng I-TEQ kg⁻¹ (74.6 ng kg⁻¹) for coffee-residue -fired boiler, and 0.0277 ng I-TEQ kg⁻¹ (0.489 ng kg⁻¹) for bagasse-fired boilers. The annual PCDD/F emission was estimated to be 208 g I-TEQ in 2020 in China, accounting for approximately 2% of the total national annual emission of PCDD/Fs. The results can be used to develop PCDD/Fs emission inventories and offer valuable insights to authorities regarding utilizing biomass in industry in the future.